Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Sci Rep. 2020 May 5;10(1):7598. doi: 10.1038/s41598-020-64564-6.
The purpose of this study was to investigate prognostic factors predicting recurrence of breast cancer, focusing on imaging factors including morphologic features, quantitative MR parameters, and clinicopathologic factors. This retrospective study was approved by our institutional review board, and the requirement to obtain informed consent was waived. A total of 267 patients with breast cancer were enrolled in this study, who underwent dynamic contrast-enhanced magnetic resonance imaging (MRI) before surgery from February 2014 to June 2016. Imaging parameters of MRI, including morphologic features, perfusion parameters, and texture analysis, were retrospectively reviewed by two expert breast radiologists. Clinicopathologic information of enrolled patients was also reviewed using medical records. Univariable and multivariable Cox proportional hazards regression analyses were used to identify factors associated with cancer recurrence. C statistics was used to discriminate low and high risk patients for disease recurrence. Using Kaplan-Meier survival analysis, disease-free survival was compared between patients who experienced recurrence and those who did not. At a median follow up of 49 months, 32 patients (12%) showed disease: six cases of ipsilateral breast or axilla recurrence, one case of contralateral breast recurrence, 24 cases of distant metastasis, and one case of both ipsilateral breast recurrence and distant metastasis. Of multiple imaging features and parameters, increased ipsilateral vascularity and higher positive skewness of texture analysis showed significant association with disease recurrence in every multivariable model regardless of tumor subtype and pathologic stage. Pathologic stage, especially if higher than stage II, showed significant association with disease recurrence and its highest hazard ratio was 3.45 [95% confidence interval (CI): 1.37-8.67, p = 0.008]. Of the multivariable models, the model including clinico-pathologic factors and both qualitative and quantitative imaging parameters showed good discrimination with a high C index value of 0.825 (95% CI: 0.755-0.896). In addition, recurrence associated factors were associated with short interval time to disease recurrence by Kaplan-Meier survival analysis. Therefore, comprehensive analysis using both clinico-pathologic factors and qualitative and quantitative imaging parameters is more effective in predicting breast cancer recurrence. Among those factors, higher pathologic stage, increased ipsilateral vascularity and higher positive skewness of texture analysis could be good predictors of breast cancer recurrence. Moreover, when these three factors are applied comprehensively, they may also be the predictors for poor survival.
本研究旨在探讨预测乳腺癌复发的预后因素,重点关注影像学因素,包括形态学特征、定量磁共振参数和临床病理因素。本回顾性研究经机构审查委员会批准,豁免了获得知情同意的要求。共纳入 267 例乳腺癌患者,这些患者于 2014 年 2 月至 2016 年 6 月在术前接受了动态对比增强磁共振成像(MRI)检查。由两位资深乳腺放射科医生对 MRI 的影像学参数(包括形态学特征、灌注参数和纹理分析)进行回顾性分析。使用病历回顾纳入患者的临床病理信息。采用单变量和多变量 Cox 比例风险回归分析确定与癌症复发相关的因素。C 统计量用于区分疾病复发的低风险和高风险患者。采用 Kaplan-Meier 生存分析比较复发组和未复发组患者的无病生存率。在中位随访 49 个月时,32 例(12%)患者发生疾病复发:6 例同侧乳房或腋窝复发,1 例对侧乳房复发,24 例远处转移,1 例同侧乳房和远处转移均复发。在每个多变量模型中,无论肿瘤亚型和病理分期如何,增加的同侧血管生成和更高的纹理分析正偏度均与疾病复发显著相关。病理分期,特别是高于 II 期,与疾病复发显著相关,其最高危险比为 3.45[95%置信区间(CI):1.37-8.67,p=0.008]。在多变量模型中,包含临床病理因素和定性及定量影像学参数的模型具有较好的区分度,C 指数值较高,为 0.825(95%CI:0.755-0.896)。此外,通过 Kaplan-Meier 生存分析发现,与疾病复发相关的因素与疾病复发的时间间隔较短有关。因此,使用临床病理因素和定性及定量影像学参数的综合分析更有效地预测乳腺癌复发。在这些因素中,较高的病理分期、同侧血管生成增加和纹理分析的正偏度较高可能是乳腺癌复发的良好预测指标。此外,当综合应用这三个因素时,它们也可能是生存不良的预测指标。